Data analytics. I never thought I will end up here. Just a short story, I have spent most of my professional time finding myself, in the sense that what I’m really passionate about. I had done some different things during my career with my core background in chemical and safety engineering. I worked as a drilling engineer in offshore and onshore rig sites dealing with geological and drilling dynamics data. I was a researcher at a German research institute dealing with experimental data. Lastly, I worked as EHS (Environmental Health Safety) consultant mostly conducting compliance audit in Germany and dealing with different client’s operational data. After a long reflection, there is only one clear similarity from what I have done so far. Yes, DATA! I enjoyed diving deep into those data and draw insights out of them.
I don’t know about you, but I believe that data is really the new oil. I can’t emphasize enough how powerful the data is, but just depend on the one who handle this. And The Data School came just right in time in my searching journey. Now, I start my data journey with the data guru!!
First Week of Training
We spent two days in the first week with the data core concept as follows. Learning the basics is what really help me understand a concept, to help me understand “Why do I have to do this?”
1. Data Structure and Terminology
I would describe data as simple as documented observations because this is the starting point where I as analyst start the work. Observing.
Those data exist in our world usually as flat files comprising rows and columns. Rows represent instances or observations; If we have data on individual students, for example, each student would count as a single observation. While, columns represent characteristics or variables. For instance, each observation, or student, has only a single characteristic: “Subject”.
Here, we were also introduced to the ETL (Extract-Transform-Load) term which is our general process flow with a big remark that it doesn’t necessarily occur in a sequence.
2. Data Sources and Architecture
3. Answering Questions with Data
As a consultant, the most important thing is of course serving client’s needs. Ensuring we are at the same page with the client is “Das A und O” in German. This will include project scope and client requirements, thus, communication is the key and please drop our assumptions or confirmation bias. Also, I found user stories concept is really helpful to help us consultant addressing stakeholders wishes. Secondly, we should plan the work and we will be less likely to have blank page syndrome.
4. Cleaning and Reshaping Data
Getting little bit technical here as we were introduced with the concept of data granularity with the help of aggregation and join.
On Thursday, we finally started to get our hand ‘dirty’ on the Tableau Prep. From the training, I have an impression that Tableau Prep is the light version of Alteryx :D. However, I did enjoy the session by doing preppin challenge myself.
On Friday or presentation day, we were given datasets to work with and at the end of the day, we have to present! A bit worry about presenting in front of the whole people of the company, but it turned out well. For me, pressure is less as long as I don't see the people because most of them are online. Haha!
That's all people for this week. I can't wait for more training materials to come!
Cheers,
Nuki